We present new multiwavelet transforms for discrete signals. The transforms are implemented in two phases: 1. Pre (post)processing which transform the scalar signal into the vector one (and back). 2.Wavelet transforms of the vector signal. Both phases are performed in a lifting manner. We use the cubic interpolatory Hermite splines as a predicting aggregate in the vector wavelet transform. We p...

JPEG-2000 is the latest image coding standard and is based on wavelet transforms and dyadic spectral decompositions. We have adapted the JPEG-2000 image coder for use with uniform transforms, by replacing the wavelet stage by lapped transforms. We set code-blocks that do not cross subband boundaries and encode the lapped transform coefficients directly as if they were wavelet ones. Results indi...

This study investigates the usefulness of wavelet transforms in phoneme recognition. Both discrete wavelet transforms (DWT) and sampled continuous wavelet transforms (SCWT) are tested. The wavelet transform is used as a part of the front-end processor which extracts feature vectors for a speakerindependent HMM-based phoneme recognizer. The results are evaluated on a portion of TIMIT corpus cons...

Invertible wavelet transforms that map integers to integers have important applications in lossless coding. In this paper we present two approaches to build integer to integer wavelet transforms. The first approach is to adapt the precoder of Laroia et al., which is used in information transmission; we combine it with expansion factors for the high and low pass band in subband filtering. The se...

The goal of Iris recognition is to recognize human identity through the textural characteristics of one’s Iris muscular patterns. Iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. Here performance comparison among various proposed techniques of Iris Recognition using the fractional coefficients of transformed Iris image...

In this paper, we study the continuity properties of wavelet transforms in the Gelfand-Shilov spaces with the use of a vanishing moment condition. Moreover, we also compute the Fourier transforms and the wavelet transforms of concrete functions in the Gelfand-Shilov spaces.

This paper presents simple wavelet based image compression method where wavelet transform is generated from orthogonal component transforms. Wavelets of DCT, DST and Real-DFT and Discrete Hartley Transform (DHT) are generated. Each generated wavelet transform is applied separately on R, G, and B plane of 256x256x3 colour image. Performance of these wavelet transforms is evaluated using two para...

Many state-of-the-art wavelet image coders use nonorthog-onal transforms for both lossy and lossless wavelet image coding 1, 2, 3, 4]. In this paper, a projection prediction is described that capitalizes on the non-orthogonality of wavelet transform basis vectors to improve the prediction of high-frequency coeecients. For lossy wavelet coders, the prediction yields improved context modeling and...

his report reviews the history, theory and mathematics of wavelet analysis. Examination of the Fourier Transform and Short-time Fourier Transform methods provides information about the evolution of the wavelet analysis technique. This overview is intended to provide readers with a basic understanding of wavelet analysis, define common wavelet terminology and describe wavelet analysis algorithms...

The quantum Fourier transform (QFT), a quantum analog of the classical Fourier transform, has been shown to be a powerful tool in developing quantum algorithms. However, in classical computing there is another class of unitary transforms, the wavelet transforms, which are every bit as useful as the Fourier transform. Wavelet transforms are used to expose the multi-scale structure of a signal an...